Optical coherence analysis and specifically optical coherence tomography (“OCT”) are becoming increasingly popular in research and clinical settings. OCT provides high-resolution, non-invasive imaging of sub-surface features of a sample. These characteristics enable such applications as industrial inspection and in vivo analysis of biological tissues and organs.
A common OCT technique is termed Fourier domain OCT (“FD-OCT,”) of which there are generally two types: Spectral Domain OCT and Swept Source OCT. In both systems, optical waves are reflected from an object or sample. These waves are referred to as OCT interference signals, or simply as interference signals. A computer produces images of two-dimensional cross sections or three-dimensional volume renderings of the sample by using information on how the waves are changed upon reflection. Spectral Domain OCT and Swept Source OCT systems differ, however, in the type of optical source that they each utilize and how the interference signals are detected.
Spectral Domain OCT systems utilize a broadband optical source and a spectrally resolving detector system to determine the different spectral components in a single axial scan (“A-scan”) of the sample. Thus, spectral Domain OCT systems usually decode the spectral components of an interference signal by spatial separation. As a result, the detector system is typically complex, as it must detect the wavelengths of all optical signals in the scan range simultaneously, and then convert them to a corresponding interference dataset. This affects the speed and performance of Spectral Domain OCT systems.
In contrast, Swept Source OCT systems encode spectral components in time, not by spatial separation. Swept Source OCT systems typically utilize wavelength (frequency) swept sources that “sweep” in the scan range. The interference signals are then typically detected by a non spectrally resolving detector or specifically a balanced detector system.
Compared to Spectral Domain OCT technology, Swept Source OCT often does not suffer from inherent sensitivity degradation at longer imaging depths, provides faster scanning speed and improved signal to noise ratio (“SNR,”), and reduces the complexity of the detector system.
Swept Source OCT systems often utilize a sampling clock, or k-clock, that is used in the sampling of the interference signals. The k-clock is typically generated by a k-clock module that generates a signal that indicates every time the swept source tunes through a predetermined frequency increment of the scan band.
Some Swept Source OCT systems use a hardware-based k-clocking to directly clock the Analog-to-Digital (“A/D”) converter of a Data Acquisition (“DAQ”) system for sampling the interference signals. Other Swept Source OCT systems sample the k-clock signals from the k-clock module in the same manner as the interference signal, creating a k-clock dataset of all sampled k-clock signals and an interference dataset of all sampled interference signals. Then, the k-clock dataset is used to resample the interference dataset. This is known as a software-based k-clocking
Swept Source OCT systems typically require this resampling or k-clock control of the interference sampling to compensate for instabilities and/or non-linearities in the tuning of the swept sources in frequency. The use of the k-clock yields interference data that are evenly spaced in the optical frequency domain, or k-space, which provides maximal SNR and axial imaging resolution for subsequent Fourier transform-based signal processing upon the acquired interference signal spectra, or interference dataset. The Fourier transform provides the “A-scan” information, or axial scan depth profile within the sample.
Because of the potentially high processing overhead that resampling of interference datasets and Fourier transform-based signal processing can incur, manufacturers of FD-OCT systems are increasingly turning to special-purpose processing units such as Field-Programmable Gate Arrays (“FPGA”), and General-Purpose Graphical Processing Units (“GPGPU,” or “GPU”). For more information, see “Scalable, High Performance Fourier Domain Optical Coherence Tomography: Why FPGAs and Not GPGPUs,” Jian Li, Marinko V. Sarunic, Lesley Shannon, School of Engineering Science, Simon Fraser University, Burnaby BC, Canada. Proceedings of the 2011 IEEE 19th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM '11, 2011.